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Abstract
The Philippine Hydrological Model is the first national-scale hydrological model of the Philippines (Scheidegger et al 2023, 2024, 2025). Its primary purpose is to quantify components of the hydrological cycle at the national level, with spatio-temporal patterns of precipitation, evapotranspiration, runoff and groundwater recharge as model outputs.
We have developed an integrated surface water-groundwater model based on the Variable Infiltration Capacity (VIC) macro-scale hydrological model (Liang et al. 1994, Hamman et al 2018), into which we have added a one-layer, 2D lateral groundwater flow model (Scheidegger et al. 2021). Groundwater recharge is derived from the interaction of the groundwater model with the VIC soil by allowing bi-directional exchange of water between the aquifer and the soil. The model is run at a 2 km grid resolution and is parameterised with, and driven by, globally available datasets describing the land surface, including soil and vegetation properties.
The model outputs include: evapotranspiration, runoff, groundwater recharge, baseflow, groundwater levels, and soil moisture.
The resulting modelling framework provides a means to develop understanding of the water resources across the Philippines and aims to support future national water resources planning.
Development of the Philippine Hydrological model began under the ‘Philippines Groundwater Outlook (PhiGO)’ project - a collaboration between the British Geological Survey (BGS), Ateneo de Manila University (ADMU), and the Philippine’s National Water Resources Board (NRWB). The project was joint-funded under the NERC-Newton and DOST-PCIEERD programme, understanding the impacts of hydrometeorological hazards in Southeast Asia (project NE/S003118/1). Under PhiGO, models of Panay and Pampanga were developed. Using subsequent funding from BGS’s International Geoscience Research and Development (IGRD) programme the model was then expanded to cover the whole of the Philippines. The latest developments have been undertaken under the Philippine Hydro Hub, a collaboration between the University of the Philippines Diliman, Ateneo de Manila University and the British Geological Survey. This work has been funded by the UK Department for Science Innovation and Technology's International Science Partnerships Fund in partnership with the British Council.
To run this model the VIC-AMBHAS-GRID version of the code is used, accessed here: https://github.com/BritishGeologicalSurvey/VIC/blob/VIC-AMBHAS-GRID/vic/extensions/AMBHAS/readme.md
More info can be found here:
References:
Hamman, J J, Nijssen, B, Bohn, T J, Gergel, D R and Mao, Y X 2018. The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility. Geoscientific Model Development 11(8), 3481-3496, https://doi.org/10.5194/gmd-11-3481-2018.
Scheidegger, Johanna. 2025 Future projections of the hydrology of the Philippines : dataset summary. Nottingham, UK, British Geological Survey, 28pp. (OR/25/010) (Unpublished)
Scheidegger, Johanna. 2024 User guide : BGS Philippine National Hydrological Model dataset. British Geological Survey, 45pp. (OR/24/023)
Scheidegger, Johanna; Barkwith, Andrew; Jackson, Christopher; Mansour, Majdi; Guzman, Aileen. 2023 Philippine National Hydrological Model. British Geological Survey, 12pp. (OR/23/053) (Unpublished)
Scheidegger, Johanna M.; Jackson, Christopher R.; Muddu, Sekhar; Tomer, Sat Kumar; Filgueira, Rosa. 2021 Integration of 2D Lateral Groundwater Flow into the Variable Infiltration Capacity (VIC) Model and Effects on Simulated Fluxes for Different Grid Resolutions and Aquifer Diffusivities. Water, 13 (5), 663. 10.3390/w13050663
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Content
README.md
VIC-AMBHAS input files for the Philippine Hydrological Model
Description of the Philippine Hydrological Model
The Philippine Hydrological Model is the first national-scale hydrological model of the Philippines. Its primary purpose is to quantify components of the hydrological cycle at the national level, with spatio-temporal patterns of precipitation, evapotranspiration, runoff and groundwater recharge as model outputs.
We have developed an integrated surface water-groundwater model based on the Variable Infiltration Capacity (VIC) macro-scale hydrological model (Liang et al. 1994, Hamman et al. 2018), into which we have added a one-layer, 2D lateral groundwater flow model. Groundwater recharge is derived from the interaction of the groundwater model with the VIC soil by allowing bi-directional exchange of water between the aquifer and the soil. The model is run at a 2 km grid resolution and is parameterised with, and driven by, globally available datasets describing the land surface, including soil and vegetation properties.
The model outputs include: evapotranspiration, runoff, groundwater recharge, baseflow, groundwater levels, and soil moisture.
To run this model the VIC-AMBHAS-GRID version of the code is used, accessed here: https://github.com/BritishGeologicalSurvey/VIC/blob/VIC-AMBHAS-GRID/vic/extensions/AMBHAS/readme.md
Description of model structure
The Philippine Hydrological Model is split into four sub-models: North, Center, South and West. These are referred to as LOCATION below. Each of these sub-models is run seperately. Within each model folder, the following sub-folders are required:
-
AMBHAS
-
AMBHAS_OUT
-
grid
-
results
-
run
The folders AMBHAS_OUT and results are empty at the start of the simulation. The contents of the other folders are described below.
Description VIC input files
The VIC input files are stored in the folder run.
-
VIC global parameters: VIC_global_params_LOCATION.txt. This is the main input file for VIC. It points VIC to the locations of other input/output files and sets parameters that govern the simulation, such as start and end dates.
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VIC parameter file: VIC_params_LOCATION.nc. Spatially distributed parameters describing the land surface.
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VIC domain file: VIC_Domain_LOCATION.nc. Domain information of VIC run.
A full description can be found here:
https://vic.readthedocs.io/en/master/Documentation/Drivers/Image/Inputs/
Description of AMBHAS input file
The groundwater input files are stored in the folder AMBHAS.
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AMBHAS global parameter file for AMBHAS: gw_global_parameters.dat
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AMBHAS parameter file: gw_LOCATION_geol.nc
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AMBHAS observation points: gw_observation.dat
A full description of the input files can be found here:
https://github.com/BritishGeologicalSurvey/VIC/blob/VIC-AMBHAS-GRID/vic/extensions/AMBHAS/readme.md
Description of Grid input files
The grid input files are stored in the folder grid.
-
Grid global parameter file: grid_global_params.dat
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Grid forcing cell numbers: Force_CellPhilippines.nc
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VIC cell numbers: VIC_CellNo_LOCATION.nc
The inclusion of the grid modules allows the model to run using forcing data at its original spatial resolution and saves the user from to re-gridding the climate data to the model extent and grid resolution. Each cell number from the forcing data, as specified in the Forcing cell numbers, then points to the coresponding VIC cell numbers, that maps the forcing cell onto the VIC grid.
A full description of the input files can be found here:
https://github.com/BritishGeologicalSurvey/VIC/blob/VIC-AMBHAS-GRID/vic/extensions/AMBHAS/readme.md
Description of Forcing data
The input files containint the climate forcing data are stored in the folder forcing_ERA5.
One netcdf file per year is provided at a six hourly time step.
Descriptions of the variables and units can be found here: https://vic.readthedocs.io/en/master/Documentation/Drivers/Image/ForcingData/
Link to the Code
VIC is written in the C prgramming language. The code can be found here: https://github.com/BritishGeologicalSurvey/VIC/tree/VIC-AMBHAS-GRID
Running the model on a Linux cluster
Advice on how to run and compile VIC can be found here:
https://vic.readthedocs.io/en/master/Documentation/Drivers/Image/RunVIC/
We run the model by using the batch script found in the run folder.
Data sources
Table 1. Description and data source of variables for the VIC global parameter file.
| # | Variable name | Source | Description |
|---|---|---|---|
| 1 | mask | Global Administrative Areas (2012) | Country and island outline |
| 2 | layer | - | - |
| 3 | run_cell | - | 1 = Run grid cell, 0 = Do not run |
| 4 | gridcell | - | Grid cell number |
| 5 | lats | - | Latitude |
| 6 | lons | - | Longitude |
| 7 | infilt | Calibration parameter | Variable infiltration parameter describing the Variable Infiltration Curve. Typical values range from 1e-5 to 0.4. |
| 8 | Ds | Dummy, not used | Fraction of Dsmax at which non-linear baseflow occurs |
| 9 | Dsmax | Dummy, not used | Maximum baseflow velocity per grid cell |
| 10 | Ws | Dummy, not used | Fraction of maximum soil moisture where non-linear baseflow occurs |
| 11 | c | Dummy, not used | Exponent used in baseflow curve (normally 2) |
| 12 | expt | Zhang and Marcel (2018) | Exponent in Campbell equation for hydraulic conductivity |
| 13 | Ksat | Zhang and Marcel (2018) | Saturated hydraulic conductivity (mm/day) |
| 14 | phi_s | Zhang and Marcel (2018) | Soil moisture diffusion parameter |
| 15 | init_moist | Porosity x layer depth | Initial soil moisture (mm) |
| 16 | elev | HydroSHEDS (Lehner et al. 2008) | Average elevation of grid cell |
| 17 | depth | - | Thickness of soil moisture layers |
| 18 | avg_T | Fick and Hijmans (2017) | Average soil temperature |
| 19 | dp | 4 m | Soil thermal damping depth |
| 20 | bubble | Derived from expt | Soil bubbling pressure |
| 21 | quartz | SoilGrids (Hengl et al. 2014) | Quartz (sand) fraction |
| 22 | bulk_density | SoilGrids (Hengl et al. 2014) | Bulk density |
| 23 | soil_density | Assumed | Soil particle density |
| 24 | off_gmt | - | Time zone offset from GMT |
| 25 | Wcr_FRACT | Zhang and Marcel (2018) | Fractional soil moisture at critical point |
| 26 | Wpwp_FRACT | Zhang and Marcel (2018) | Fractional soil moisture at wilting point |
| 27 | rough | 0.001 | Bare soil surface roughness |
| 28 | snow_rough | 0 | Snow surface roughness |
| 29 | annual_prec | Fick and Hijmans (2017) | Average annual precipitation |
| 30 | resid_moist | Zhang and Marcel (2018) | Residual soil moisture |
| 31 | fs_active | 0 | Frozen soil flag |
| 32 | cellnum | Same as gridcell | Grid cell number |
| 33 | AreaFract | 1 | Elevation band area fraction |
| 34 | elevation | HydroSHEDS (2008) | Mean elevation of elevation band |
| 35 | Pfactor | 1 | Precipitation fraction per band |
| 36 | veg_descr | MODIS land cover | Land cover classification |
| 37 | Nveg | 1 | Number of vegetation tiles |
| 38 | Cv | 1 | Vegetation cover fraction |
| 39 | root_depth | Fan et al. (2017) | Root zone depth |
| 40 | root_fract | Calculated | Root fraction per layer |
| 41 | LAI | Copernicus | Leaf Area Index |
| 42 | overstory | MODIS + VIC | Overstory flag |
| 43 | rarc | VIC veg library | Architectural resistance |
| 44 | rmin | VIC veg library | Minimum stomatal resistance |
| 45 | wind_h | VIC veg library | Wind measurement height |
| 46 | RGL | VIC parameters | Radiation threshold for transpiration |
| 47 | rad_atten | Default 0.5 | Radiation attenuation factor |
| 48 | wind_atten | Default 0.5 | Wind attenuation factor |
| 49 | trunk_ratio | Default 0.2 | Trunk height ratio |
| 50 | albedo | Copernicus | Vegetation albedo |
| 51 | veg_rough | Healey et al. (2015) | Vegetation roughness length |
| 52 | displacement | Healey et al. (2015) | Vegetation displacement height |
Table 2. Parameters and sources for the Groundwater model coupled to VIC.
| # | Variable name | Units | Description | Data source |
|---|---|---|---|---|
| 1 | Sy | - | Specific yield | Groundwater availability map (1986) |
| 2 | Trans | m2/day | Transmissivity | Dummy |
| 3 | K | m/day | Hydraulic conductivity | Groundwater availability map (1986) |
| 4 | mask | - | Active model domain mask | - |
| 5 | dem | m | Digital elevation model | HydroSHEDS (2008) |
| 6 | zbase | m | Base of aquifer above datum | 100 m |
| 7 | zriver | m | River elevation | DEM minus 5 m |
| 8 | driver | m | River bed thickness | 1 m |
| 9 | C_eff | 1/day | Conductance of effluent rivers | Calibration |
| 10 | C_in | 1/day | Conductance of influent rivers | Calibration |
| 11 | C_leak_eff | 1/day | Effluent leakage conductance | 0 |
| 12 | C_leak_in | 1/day | Influent leakage conductance | 0 |
| 13 | headBC | m | Specified head boundary | 0 at coast |
| 14 | river_area | m2 | River cell area | Grid cell area |
| 15 | aquifer_map | - | Aquifer type (1 unconfined, 0 confined) | 1 |
| 16 | c_n | m | Cell center distance north | Calculated |
| 17 | c_e | m | Cell center distance east | Calculated |
| 18 | e_n | m | Cell north edge length | Calculated |
| 19 | e_e | m | Cell east edge length | Calculated |
| 20 | cell_area | m2 | Grid cell area | Calculated |
| 21 | z_soil | m | VIC soil depth | 2 m |
| 22 | Sy_soil | - | Soil specific yield | Zhang and Marcel (2018) |
Table 3. Parameters and sources for the forcing file in VIC.
| # | Variable name | Units | Description | Data source |
|---|---|---|---|---|
| 1 | mask | - | Model domain mask | - |
| 2 | prcp | mm/step | Total precipitation | Hersbach et al. (2018) |
| 3 | tas | C | Average air temperature | Hersbach et al. (2018) |
| 4 | dswrf | W/m2 | Incoming shortwave radiation | Hersbach et al. (2018) |
| 5 | dlwrf | W/m2 | Incoming longwave radiation | Hersbach et al. (2018) |
| 6 | pres | kPa | Atmospheric pressure | Hersbach et al. (2018) |
| 7 | vp | kPa | Vapor pressure | Hersbach et al. (2018) |
| 8 | wind | m/s | Wind speed | Hersbach et al. (2018) |
References
British Geological Survey: Philippine National Hydrological Model Dataset, NERC EDS National Geoscience Data Centre, https://doi.org/10.5285/9a8dffe7-5bf7-496c-9d0a-99dea86c631c, 2024.
Bureau of Mines and Geo-Sciences and Ministry of Natural Resources: Groundwater availability map of the Philippines, Bureau of Mines and Geo-Sciences, Geology and Mineral Resources of the Philippines. Volume two Mineral Resources. Plate supplement XVI, Metro Manila, Philippines, 1986.
Fan, Y., Miguez-Macho, G., Jobbágy, E. G., Jackson, R. B., and Otero-Casal, C.: Hydrologic regulation of plant rooting depth, Proceedings of the National Academy of Sciences, 114, 10572, https://doi.org/10.1073/pnas.1712381114, 2017a.
Fan, Y., Miguez-Macho, G., Jobbágy, E. G., Jackson, R. B., and Otero-Casal, C.: Hydrologic regulation of plant rooting depth [dataset], 2017b.
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas, International Journal of Climatology, 37, 4302-4315, https://doi.org/10.1002/joc.5086, 2017.
Friedl, M. and Sulla-Menashe, D.: MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006. 2015, distributed by NASA EOSDIS Land Processes DAAC [dataset], https://doi.org/10.5067/MODIS/MCD12C1.006, 2015.
Global Administrative Areas: GADM database of Global Administrative Areas, version 2.0., 2012.
Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. X.: The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geoscientific Model Development, 11, 3481-3496, https://doi.org/10.5194/gmd-11-3481-2018, 2018.
Healey, S. P., M.W. Hernandez, D.P. Edwards, M.A. Lefsky, E. Freeman, P.L. Patterson, E.J. Lindquist, and Lister., A. J.: CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008, https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1271 [dataset], https://doi.org/10.3334/ORNLDAAC/1271, 2015.
Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G. B., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J. G., Walsh, M. G., and Gonzalez, M. R.: SoilGrids1km--global soil information based on automated mapping, PLoS One, 9, e105992, https://doi.org/10.1371/journal.pone.0105992, 2014.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [dataset], https://doi.org/10.24381/cds.adbb2d47, 2018.
Lehner, B., Verdin, K., Jarvis, A. (2008). New global hydrography derived from spaceborne elevation data. Eos, Transactions, American Geophysical Union, 89(10): 93–94. https://doi.org/10.1029/2008eo100001.
Liang, X.; Lettenmaier, D. P.; Wood, E. F. and Burges, S. J. 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, doi:10.1029/94JD00483.
Lohmann, D., Nolte-Holube, R., and Raschke, E.: A large-scale horizontal routing model to be coupled to land surface parametrization schemes, Tellus, Series A: Dynamic Meteorology and Oceanography, 48, 708-721, https://doi.org/10.3402/tellusa.v48i5.12200, 1996.
Scheidegger, Johanna. 2025 Future projections of the hydrology of the Philippines: dataset summary. Nottingham, UK, British Geological Survey, 28pp. (OR/25/010) (Unpublished).
Scheidegger, Johanna. 2024 User guide: BGS Philippine National Hydrological Model dataset. British Geological Survey, 45pp. (OR/24/023).
Scheidegger, J., Barkwith, A., Jackson, C., Mansour, M., and Guzman, A.: Philippine National Hydrological Model, British Geological Survey, 2023.
Scheidegger, J. M., Jackson, C. R., Muddu, S., Tomer, S. K., and Filgueira, R.: Integration of 2D Lateral Groundwater Flow into the Variable Infiltration Capacity (VIC) Model and Effects on Simulated Fluxes for Different Grid Resolutions and Aquifer Diffusivities, Water, 13, 663, https://doi.org/10.3390/w13050663, 2021.
Smets, B. and Sánchez-Zapero, J.: Copernicus Global Land Operations "Vegetation and Energy" ”CGLOPS-1”, Copernicus [dataset], 2018.
Smets, B., Verger, A., Camacho, F., Van der Goten, R., and Jacobs, T.: Copernicus Global Land Operations "Vegetation and Energy", Copernicus [dataset], https://land.copernicus.eu/global/products/lai, 2019.
Zhang, Y. and Marcel, G. S.: A High-Resolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically-Based Water Retention Model (V1), Harvard Dataverse [dataset], https://doi.org/10.1002/joc.443610.7910/DVN/UI5LCE, 2018.
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